Table of Content

1. Introduction
2. Discrete Time-Signals and Systems
3. The z-Transform
4. Sampling of Continuous-Time Signals
5. Transform Analysis of Linear Time-Invariant Systems
6. Structures for Discrete-Time Systems
7. Filter Design Techniques
8. The Discrete Fourier Transform
9. Computation of the Discrete Fourier Transform
10. Fourier Analysis of Signals Using the Discrete Fourier Transform
11. Parametric Signal Modeling
12. Discrete Hilbert Transforms
Appendix A. Random Signals
Appendix B. Continuous-Time Filters
Appendix C. Answers to Selected Basic Problems

Salient Features

• Chapter organization is self-contained — A background of advanced calculus and exposure to linear system theory for continuous-time signals is inferred.
• Material on:
• Multi-rate filtering banks.
• The discrete cosine transform.
• Noise-shaping sampling strategies.
• Includes several dozen problem-solving examples that not only illustrate key points, but demonstrate approaches to typical problems related to the material.
• Contains a wealth of class-tested problems which are the best produced over decades of undergraduate and graduate signal processing classes at MIT and Georgia Tech.
• Problems are organized by level of difficulty into separate categories:
• Basic Problems with Answers to allow students to check their results, but not solutions (20 per chapter).
• Basic Problems - without answers.
• Advanced Problems - provide an opportunity for students to understand.
• Extension Problems - start from the discussion in the text and lead students beyond to glimpse some advanced areas of signal processing.
• Offers a wealth of problems and examples.
•